In this presentation you will learn the basics of working with nested data, such as students within classes, customers within households, or patients within clinics through the use of multilevel models. Multilevel models can accommodate correlation among nested units through random intercepts and slopes, and generalize easily to 2, 3, or more levels of nesting. These models represent a statistically efficient and powerful way to test your key hypotheses while accounting for the hierarchical nesting of the design. The GLIMMIX procedure is used to demonstrate analyses in SAS.
Catherine “Cat” Truxillo is the Director of Advanced Analytics Education at SAS, and an award-winning trainer with over 25 years of experience consulting and teaching in many industries. She specializes in mixed models, multivariate analysis, and data science team building. Her students say she has a gift for breaking complex topics down to manageable bits.